|
--- |
|
license: apache-2.0 |
|
tags: |
|
- summarization |
|
- generated_from_trainer |
|
metrics: |
|
- rouge |
|
model-index: |
|
- name: mt5-small-finetuned-amazon-en-es |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# mt5-small-finetuned-amazon-en-es |
|
|
|
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 3.0255 |
|
- Rouge1: 17.469 |
|
- Rouge2: 8.5134 |
|
- Rougel: 17.1167 |
|
- Rougelsum: 17.2481 |
|
|
|
## Model description |
|
|
|
More information needed |
|
|
|
## Intended uses & limitations |
|
|
|
More information needed |
|
|
|
## Training and evaluation data |
|
|
|
More information needed |
|
|
|
## Training procedure |
|
|
|
### Training hyperparameters |
|
|
|
The following hyperparameters were used during training: |
|
- learning_rate: 5.6e-05 |
|
- train_batch_size: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 8 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:| |
|
| 8.094 | 1.0 | 1209 | 3.2933 | 12.7976 | 5.1617 | 12.4199 | 12.5113 | |
|
| 3.9263 | 2.0 | 2418 | 3.1487 | 16.2082 | 8.3215 | 15.744 | 15.807 | |
|
| 3.599 | 3.0 | 3627 | 3.0789 | 16.9706 | 8.2425 | 16.3972 | 16.4067 | |
|
| 3.429 | 4.0 | 4836 | 3.0492 | 17.2122 | 8.7398 | 16.7892 | 16.795 | |
|
| 3.3279 | 5.0 | 6045 | 3.0384 | 17.5381 | 8.7438 | 17.0764 | 17.1831 | |
|
| 3.2518 | 6.0 | 7254 | 3.0343 | 17.0966 | 8.5622 | 16.7016 | 16.8022 | |
|
| 3.2084 | 7.0 | 8463 | 3.0255 | 16.7713 | 8.0472 | 16.3159 | 16.4091 | |
|
| 3.1839 | 8.0 | 9672 | 3.0255 | 17.469 | 8.5134 | 17.1167 | 17.2481 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.18.0 |
|
- Pytorch 1.10.0+cu111 |
|
- Datasets 2.1.0 |
|
- Tokenizers 0.12.1 |
|
|
